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Found 8 papers, 4 papers with code
DIRECT: Direct and Indirect Responses in Conversational Text Corpus
We create a large-scale dialogue corpus that provides pragmatic paraphrases to advance technology for understanding the underlying intentions of users.
Predicting Parking Lot Availability by Graph-to-Sequence Model: A Case Study with SmartSantander
Nowadays, so as to improve services and urban areas livability, multiple smart city initiatives are being carried out throughout the world.
Distinct Label Representations for Few-Shot Text Classification
Few-shot text classification aims to classify inputs whose label has only a few examples.
Consistent Response Generation with Controlled Specificity
To control the specificity of generated responses, we add the distant supervision based on the co-occurrence degree and a PMI-based word prediction mechanism to a sequence-to-sequence model.
Text Classification with Negative Supervision
Advanced pre-trained models for text representation have achieved state-of-the-art performance on various text classification tasks.
Responsive and Self-Expressive Dialogue Generation
Specifically, our model generates domain-aware and sentiment-rich responses.
Relevant and Informative Response Generation using Pointwise Mutual Information
A sequence-to-sequence model tends to generate generic responses with little information for input utterances.
Dialogue-Act Prediction of Future Responses Based on Conversation History
One significant drawback of such a neural network based approach is that the response generation process is a black-box, and how a specific response is generated is unclear.
